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Risk visualization: When actuarial science meets visual analytics
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Journal of Computer Science & Systems Biology

ISSN: 0974-7230

Open Access

Risk visualization: When actuarial science meets visual analytics


Joint Event on 7th International Conference on Biostatistics and Bioinformatics & 7th International Conference on Big Data Analytics & Data Mining

September 26-27, 2018 | Chicago, USA

Nicolas Wesner

Mazars Actuariat, France

Keynote: J Comput Sci Syst Biol

Abstract :

Actuarial Science aims at measuring and modeling financial risk with the use of statistical and mathematical models. Unlike traditional sciences like Physics or Biology, its main raw material, risk, is not directly observable and inherently subjective. It is perhaps for some of those reasons that the concept of risk visualization has not received much attention in the Literature. This paper argues that risk visualization can find many practical applications in finance and insurance, namely for communicating about risk (internally, toward the senior management or third parties), risk identification and management (through comprehensive, real-time, interactive Risk Dashboard) and informed decision making (multi-objective optimization). After reviewing the foundations of visual analytics and its appeal for risk analysis and risk management, applications of dimensionality reduction and clustering techniques to practical problems of risk monitoring in finance and insurance are presented.

Biography :

Nicolas Wesner has completed his PhD in Economics at the University of Paris X Nanterre and is an Associate Actuary since 2011. He is the head of the Pension Department of Mazars Actuariat an actuarial consulting firm that provides financial services for Banks, Insurance companies and Pension Funds. He has published chapters or papers in reputed Journals on various subjects such as econometrics, quantitative finance, insurance and pension and data mining.

E-mail: nicolas.wesner@mazars.fr

 

Google Scholar citation report
Citations: 2279

Journal of Computer Science & Systems Biology received 2279 citations as per Google Scholar report

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